Profile of the Effectiveness Factor under Optimal Operating Conditions for the Conversion of Ortho-Xylene to Phthalic Anhydride in a Fixed-Bed Tubular Reactor

• Autores: Carrasco-Venegas, Luis Américo, Vásquez-Alvarez, Elsa, González-Fernández, José Vulfrano, Castañeda Perez, Luz Genara, Medina-Collana, Juan Taumaturgo, Palomino-Hernández, Guido, Martínez-Hilario, Daril Giovanni, Trujillo-Pérez, Salvador Apolinar
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad Nacional Federico Villarreal
• Repositorio: UNFV-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.unfv.edu.pe:20.500.13084/8682
• Enlace del recurso: https://hdl.handle.net/20.500.13084/8682; https://doi.org/10.3390/chemengineering8020035
• Nivel de acceso: acceso abierto
• Materia: Mass balance; Energy balances; Effectiveness factor; Phthalic anhydride; https://purl.org/pe-repo/ocde/ford#1.04.00

The objective of this research is to find the effectiveness factor of the catalyst particles for the most favorable conditions of the phthalic anhydride production in a fixed bed reactor, with the aim of achieving the highest rate of phthalic anhydride production compared to other secondary products and analyzing the areas of lower effectiveness for the modification of the reactor design. Initially, the material and the energy balances in the catalytic bed are solved to obtain the concentration and temperature profiles based on the radius and length of the reactor, using polymath software(Polymath® v6.2 Software Minitab 19 Matlab 2019) with the data from literature. Once the profiles reproducibility was verified using the initial data (inlet temperature, pressure in the reactor, reactor wall temperature, reactor radius and mass flow rate) the experimental design 35 carry out, which generates 243 “experiments”, whose response variable (phthalic anhydride concentration) was obtained using Matlab. Subsequently, the variables were analyzed using the Minitab 18® that, through the response surface analysis method, allowed us to obtain the optimal values of the tested variables. Then, Subsequently, material and energy balances coupled with Fourier and Fick’s laws, along with the effectiveness factor equation, were applied, resulting in the generation of 9 coupled differential equations. Upon implementing the finite difference method, this yielded 90 nonlinear algebraic equations, which were solved using the Polymath software. A total of 78 particles were preselected based on their radial and axial positions to determine the effectiveness factor profile, with values ranging from 0.83 to near unity. The lower values correspond to the points with higher temperature, as evidenced by the calculations performed.